Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "42" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 51 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 49 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459866 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.053019 | 1.405089 | -0.183925 | 1.825882 | 0.255206 | -0.233747 | 0.629655 | 0.585188 | 0.7236 | 0.7012 | 0.3885 | nan | nan |
| 2459865 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.261525 | 1.974646 | 6.054942 | 7.584273 | -0.883473 | -0.463252 | 0.160774 | 0.606782 | 0.7419 | 0.7220 | 0.3547 | nan | nan |
| 2459864 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.324066 | 1.365867 | -1.291831 | 0.025836 | -0.487202 | -0.743498 | -0.358277 | -0.440310 | 0.7213 | 0.6947 | 0.4058 | nan | nan |
| 2459863 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459862 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.107787 | 3.705062 | -1.379885 | -0.333475 | -0.320507 | -0.513766 | 0.042497 | -0.686117 | 0.6994 | 0.7027 | 0.4091 | nan | nan |
| 2459861 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.271591 | 2.138785 | -0.217287 | 0.591581 | 0.049173 | -0.019818 | 0.052769 | -0.598730 | 0.7288 | 0.6872 | 0.4077 | nan | nan |
| 2459860 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.176887 | 1.866186 | -0.720241 | -0.404236 | -1.042392 | -0.059821 | 0.214291 | -0.800620 | 0.7356 | 0.6836 | 0.4079 | nan | nan |
| 2459859 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 192.631169 | 193.111253 | inf | inf | 3120.940844 | 3120.904326 | 5590.618141 | 5578.973442 | nan | nan | nan | nan | nan |
| 2459858 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.058323 | 2.288173 | -0.339996 | 0.517711 | -0.136542 | 0.311442 | 0.218912 | -0.468333 | 0.7477 | 0.6923 | 0.4183 | 1.804963 | 1.582007 |
| 2459857 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 1.343843 | 0.942210 | 0.296749 | 0.332088 | 1.621338 | 0.205920 | -0.098604 | 0.890919 | 0.0364 | 0.0419 | 0.0080 | nan | nan |
| 2459856 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.43% | 0.00% | -0.066340 | 3.270315 | -0.230002 | -0.475790 | -0.459867 | -0.464665 | 0.185056 | -0.964444 | 0.7408 | 0.7044 | 0.4050 | 1.835258 | 1.515874 |
| 2459855 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.187997 | 4.525428 | -0.736248 | -0.655686 | 0.106807 | -0.827968 | -0.283890 | -0.919537 | 0.7258 | 0.7188 | 0.4376 | 3.559543 | 2.697667 |
| 2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.278374 | 4.557133 | 0.379240 | -0.673260 | -0.469197 | -0.645812 | 0.362328 | -0.431567 | 0.7423 | 0.7453 | 0.4424 | 3.555287 | 2.682393 |
| 2459853 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.027486 | 2.585584 | 0.889812 | -0.714043 | -0.886527 | -0.761142 | 0.351409 | -0.766632 | 0.7628 | 0.6951 | 0.4264 | 1.797738 | 1.565882 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 1.08% | -1.145031 | 0.519121 | 0.751773 | -0.914073 | -0.559752 | -0.971190 | -0.405213 | -1.047078 | 0.8505 | 0.8444 | 0.2341 | 3.339932 | 3.088514 |
| 2459851 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 11.76% | 0.00% | -0.442875 | 1.105157 | 1.262491 | -0.741259 | -1.209218 | -0.787821 | -0.065839 | -0.408442 | 0.7843 | 0.7574 | 0.3325 | 1.741809 | 1.579764 |
| 2459850 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 18.02% | 0.58% | -0.266070 | 1.888864 | 0.873495 | -0.709893 | -1.091268 | -0.940735 | -0.537863 | -1.349396 | 0.7654 | 0.7597 | 0.3492 | 1.816754 | 1.563282 |
| 2459849 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 16.67% | 0.00% | -0.108400 | 2.194029 | 3.894761 | -0.422884 | -0.521941 | -0.847880 | -0.188107 | -1.216085 | 0.7649 | 0.7525 | 0.3564 | 1.428733 | 1.372223 |
| 2459848 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 30.15% | 9.05% | -0.105224 | 2.895065 | 2.852055 | 0.596659 | -0.579146 | -0.547142 | -0.428143 | -1.068067 | 0.7462 | 0.7523 | 0.3762 | 1.398944 | 1.345444 |
| 2459847 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.21% | 0.53% | -0.003775 | 2.734448 | 2.326079 | 0.662841 | 0.681680 | -0.004588 | 0.137745 | -0.795644 | 0.7472 | 0.6878 | 0.4321 | 1.574099 | 1.444072 |
| 2459846 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 33.33% | 0.00% | -1.303603 | 0.810121 | 1.960520 | 0.484628 | -0.879827 | -0.702632 | -0.696223 | -0.597901 | 0.8618 | 0.6956 | 0.4741 | 1.666949 | 1.419789 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.271444 | 3.394798 | 4.277667 | 0.627580 | -0.216240 | -0.555999 | 0.009207 | -1.303006 | 0.7615 | 0.7600 | 0.3691 | 3.137707 | 2.982014 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 5.916293 | 1.557649 | 0.304466 | 2.279350 | 1.780745 | 0.435954 | 0.262541 | 1.450229 | 0.0386 | 0.0584 | 0.0208 | nan | nan |
| 2459843 | digital_ok | 0.00% | 0.66% | 0.66% | 0.00% | 15.22% | 10.33% | 0.024789 | 3.678843 | 1.132447 | 0.108275 | -0.032715 | -0.143365 | -1.082316 | -1.096265 | 0.7677 | 0.7569 | 0.3835 | 1.904659 | 1.762678 |
| 2459838 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 69.309013 | 62.151226 | 70.930823 | 64.345566 | 64.413016 | 66.596606 | 673.608928 | 560.515782 | 0.0170 | 0.0166 | 0.0003 | 1.149828 | 1.156560 |
| 2459833 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 1.657557 | 0.823885 | -0.361601 | 0.712162 | 1.392609 | -0.024759 | -0.397511 | 0.773309 | 0.0380 | 0.0657 | 0.0057 | nan | nan |
| 2459832 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.647750 | 1.618223 | 0.616022 | 0.496619 | -0.649778 | -0.917434 | 0.017720 | -0.005353 | 0.0940 | 0.0956 | 0.0224 | 1.198877 | 1.201108 |
| 2459831 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 0.908284 | 2.342708 | 1.676880 | 3.394467 | 6.589157 | 9.776003 | 0.571298 | 1.742219 | 0.0306 | 0.0339 | 0.0022 | nan | nan |
| 2459830 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.534788 | 1.138584 | 1.452228 | 1.045984 | -0.994306 | -0.262930 | -0.376689 | -0.495111 | 0.0948 | 0.0939 | 0.0276 | 1.268357 | 1.264252 |
| 2459829 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.078622 | 4.414393 | 1.421906 | 0.913535 | -0.806385 | 0.211464 | 0.977025 | 0.269644 | 0.0887 | 0.1005 | 0.0172 | 44.532430 | 29.535897 |
| 2459828 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.517864 | 0.853057 | 1.507593 | 1.129695 | -0.151897 | -0.278920 | -0.435354 | -0.473184 | 0.0926 | 0.0878 | 0.0214 | 1.228978 | 1.212900 |
| 2459827 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.044125 | 3.501847 | 2.498898 | 1.044535 | -0.758104 | -0.370292 | -0.471635 | -0.587906 | 0.0903 | 0.1026 | 0.0178 | 1.253100 | 1.247706 |
| 2459826 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.589425 | 0.475602 | 2.232004 | 1.063372 | -0.590714 | -1.055549 | -0.814664 | -0.669702 | 0.0884 | 0.0947 | 0.0259 | 1.238421 | 1.229531 |
| 2459825 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.701466 | 0.398313 | 0.912295 | 0.969199 | -0.894522 | -0.744771 | -0.880764 | -0.875731 | 0.0989 | 0.0968 | 0.0227 | 1.170320 | 1.163606 |
| 2459824 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.366805 | 3.904774 | 0.868805 | 0.372363 | -1.032085 | 0.507261 | -0.346585 | -0.796806 | 0.0913 | 0.1159 | 0.0163 | 1.191546 | 1.190896 |
| 2459823 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.953798 | 0.011050 | 2.093095 | 1.082141 | -0.218083 | 1.439711 | -1.429974 | -0.034195 | 0.0924 | 0.1085 | 0.0235 | 1.207239 | 1.222951 |
| 2459822 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.800563 | 0.302593 | 2.205488 | 1.317262 | 0.113018 | -0.463016 | -0.194571 | -0.900240 | 0.1105 | 0.1072 | 0.0249 | 1.191274 | 1.192155 |
| 2459821 | digital_ok | 0.00% | 11.29% | 11.29% | 0.00% | 13.16% | 5.26% | -0.357206 | 0.773526 | 2.178970 | 0.905260 | -0.831677 | -0.731175 | -1.246652 | -1.496491 | 0.7306 | 0.5893 | 0.4442 | 2.325164 | 1.957930 |
| 2459820 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 2.67% | -0.142509 | 2.732657 | 2.319937 | 1.004789 | -0.355026 | -0.305844 | -0.528322 | -0.630203 | 0.7891 | 0.6911 | 0.4210 | 1.730691 | 1.618926 |
| 2459817 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 13.16% | -0.537521 | 0.439101 | 1.627145 | 0.936003 | -0.000503 | -1.426657 | -0.639415 | -0.672627 | 0.8303 | 0.6967 | 0.4960 | 2.097621 | 1.919494 |
| 2459816 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 9.30% | -0.038439 | 0.753746 | 1.615341 | 1.213165 | 0.170600 | 0.197159 | -0.834886 | -0.582170 | 0.8507 | 0.6066 | 0.5844 | 1.803835 | 1.540317 |
| 2459815 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 23.68% | -0.831144 | 0.248914 | 1.417907 | 1.036181 | -0.153947 | -0.395628 | -1.079795 | -0.011804 | 0.8214 | 0.6992 | 0.5073 | 2.480222 | 2.153053 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.21% | 0.00% | -0.636099 | 2.600524 | 1.476458 | 0.315808 | -0.053641 | -0.345669 | -0.423932 | -0.075846 | 0.7946 | 0.7013 | 0.4328 | 1.933833 | 1.571006 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Power | 1.825882 | 1.405089 | -0.053019 | 1.825882 | -0.183925 | -0.233747 | 0.255206 | 0.585188 | 0.629655 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Power | 7.584273 | -0.261525 | 1.974646 | 6.054942 | 7.584273 | -0.883473 | -0.463252 | 0.160774 | 0.606782 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 1.365867 | 1.365867 | -0.324066 | 0.025836 | -1.291831 | -0.743498 | -0.487202 | -0.440310 | -0.358277 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 3.705062 | -0.107787 | 3.705062 | -1.379885 | -0.333475 | -0.320507 | -0.513766 | 0.042497 | -0.686117 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 2.138785 | 2.138785 | -0.271591 | 0.591581 | -0.217287 | -0.019818 | 0.049173 | -0.598730 | 0.052769 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 1.866186 | -0.176887 | 1.866186 | -0.720241 | -0.404236 | -1.042392 | -0.059821 | 0.214291 | -0.800620 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | inf | 192.631169 | 193.111253 | inf | inf | 3120.940844 | 3120.904326 | 5590.618141 | 5578.973442 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 2.288173 | 2.288173 | -0.058323 | 0.517711 | -0.339996 | 0.311442 | -0.136542 | -0.468333 | 0.218912 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Temporal Variability | 1.621338 | 0.942210 | 1.343843 | 0.332088 | 0.296749 | 0.205920 | 1.621338 | 0.890919 | -0.098604 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 3.270315 | -0.066340 | 3.270315 | -0.230002 | -0.475790 | -0.459867 | -0.464665 | 0.185056 | -0.964444 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 4.525428 | 4.525428 | -0.187997 | -0.655686 | -0.736248 | -0.827968 | 0.106807 | -0.919537 | -0.283890 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 4.557133 | 4.557133 | -0.278374 | -0.673260 | 0.379240 | -0.645812 | -0.469197 | -0.431567 | 0.362328 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 2.585584 | 2.585584 | 0.027486 | -0.714043 | 0.889812 | -0.761142 | -0.886527 | -0.766632 | 0.351409 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 0.751773 | -1.145031 | 0.519121 | 0.751773 | -0.914073 | -0.559752 | -0.971190 | -0.405213 | -1.047078 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 1.262491 | -0.442875 | 1.105157 | 1.262491 | -0.741259 | -1.209218 | -0.787821 | -0.065839 | -0.408442 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 1.888864 | -0.266070 | 1.888864 | 0.873495 | -0.709893 | -1.091268 | -0.940735 | -0.537863 | -1.349396 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 3.894761 | -0.108400 | 2.194029 | 3.894761 | -0.422884 | -0.521941 | -0.847880 | -0.188107 | -1.216085 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 2.895065 | 2.895065 | -0.105224 | 0.596659 | 2.852055 | -0.547142 | -0.579146 | -1.068067 | -0.428143 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 2.734448 | 2.734448 | -0.003775 | 0.662841 | 2.326079 | -0.004588 | 0.681680 | -0.795644 | 0.137745 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 1.960520 | -1.303603 | 0.810121 | 1.960520 | 0.484628 | -0.879827 | -0.702632 | -0.696223 | -0.597901 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 4.277667 | 3.394798 | 0.271444 | 0.627580 | 4.277667 | -0.555999 | -0.216240 | -1.303006 | 0.009207 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Shape | 5.916293 | 5.916293 | 1.557649 | 0.304466 | 2.279350 | 1.780745 | 0.435954 | 0.262541 | 1.450229 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 3.678843 | 3.678843 | 0.024789 | 0.108275 | 1.132447 | -0.143365 | -0.032715 | -1.096265 | -1.082316 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Temporal Discontinuties | 673.608928 | 62.151226 | 69.309013 | 64.345566 | 70.930823 | 66.596606 | 64.413016 | 560.515782 | 673.608928 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Shape | 1.657557 | 0.823885 | 1.657557 | 0.712162 | -0.361601 | -0.024759 | 1.392609 | 0.773309 | -0.397511 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 1.618223 | -0.647750 | 1.618223 | 0.616022 | 0.496619 | -0.649778 | -0.917434 | 0.017720 | -0.005353 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Temporal Variability | 9.776003 | 0.908284 | 2.342708 | 1.676880 | 3.394467 | 6.589157 | 9.776003 | 0.571298 | 1.742219 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 1.452228 | -0.534788 | 1.138584 | 1.452228 | 1.045984 | -0.994306 | -0.262930 | -0.376689 | -0.495111 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 4.414393 | 4.414393 | -0.078622 | 0.913535 | 1.421906 | 0.211464 | -0.806385 | 0.269644 | 0.977025 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 1.507593 | 0.853057 | -0.517864 | 1.129695 | 1.507593 | -0.278920 | -0.151897 | -0.473184 | -0.435354 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 3.501847 | 0.044125 | 3.501847 | 2.498898 | 1.044535 | -0.758104 | -0.370292 | -0.471635 | -0.587906 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 2.232004 | 0.475602 | -0.589425 | 1.063372 | 2.232004 | -1.055549 | -0.590714 | -0.669702 | -0.814664 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Power | 0.969199 | 0.398313 | -0.701466 | 0.969199 | 0.912295 | -0.744771 | -0.894522 | -0.875731 | -0.880764 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 3.904774 | 0.366805 | 3.904774 | 0.868805 | 0.372363 | -1.032085 | 0.507261 | -0.346585 | -0.796806 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 2.093095 | 0.011050 | -0.953798 | 1.082141 | 2.093095 | 1.439711 | -0.218083 | -0.034195 | -1.429974 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 2.205488 | -0.800563 | 0.302593 | 2.205488 | 1.317262 | 0.113018 | -0.463016 | -0.194571 | -0.900240 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 2.178970 | 0.773526 | -0.357206 | 0.905260 | 2.178970 | -0.731175 | -0.831677 | -1.496491 | -1.246652 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 2.732657 | -0.142509 | 2.732657 | 2.319937 | 1.004789 | -0.355026 | -0.305844 | -0.528322 | -0.630203 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 1.627145 | -0.537521 | 0.439101 | 1.627145 | 0.936003 | -0.000503 | -1.426657 | -0.639415 | -0.672627 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 1.615341 | 0.753746 | -0.038439 | 1.213165 | 1.615341 | 0.197159 | 0.170600 | -0.582170 | -0.834886 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | ee Power | 1.417907 | 0.248914 | -0.831144 | 1.036181 | 1.417907 | -0.395628 | -0.153947 | -0.011804 | -1.079795 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 42 | N04 | digital_ok | nn Shape | 2.600524 | 2.600524 | -0.636099 | 0.315808 | 1.476458 | -0.345669 | -0.053641 | -0.075846 | -0.423932 |